The secret to site selection in such a competitive market is based on the ability to analyze the right data and be able to understand and interpret the site selection strategies of nearby locations to stay ahead of their expansion plans and gain a competitive advantage.
Where? This is the fundamental question that guides any site selection decision.
Retailers need to use predictive modeling and combine it with business, customer, and market data in order to forecast sales or new businesses profitability.
Predictive modelingis a highly effective way to identify a suitable area for expansion strategies, as it has become a vital tool for narrowing down hundreds of potential sites or even a single site. When a potential site is identified, it’s combined with additional layers of data to determine if it meets the model’s requirements, sales performance targets, and other critical factors for any business requirements. Read the full article here
Location analytics is taking its place as a key tool for identifying what consumers want and need, regardless of their wealth or demographic status. COVID-19 has led to completely unexpected behavioral changes.
How can location intelligence help in the recovery of any type of business?
Supermarkets can apply location intelligence techniques and footfall analytics to understand consumer mobility patterns, generate efficient site selection strategies, understand the performance of their stores, and estimate competitor turnover.
The correlation between foot traffic visitation, sales, and the success of retail supermarkets have been studied and proven, so the development of this type of analysis has become a priority in the site selection process and expansion strategies.
Footfall analytics and POI characterization through Big Data are being used by different business sectors in order to make smarter business decisions and thereby maximize their revenues and optimize their costs.
Case Study: POI analysis of N1 City in Cape Town, South Africa
Foot traffic analytics and point-of-interest analytics help large chains supplying contractor-grade building materials and home improvement products measure footfall and understand consumer behavior patterns in any given zone of interest or point of sale.
Footfall analytics have revolutionized the way retailers implement site selection, commercial and operational strategies in the quick-service restaurant franchise market.
The correlation between location and footfall analytics, visits, sales, and the success of retail fast-food franchises have been studied and proven, so the development of this type of analysis has become a priority in the site selection process and expansion strategies.
POI characterization through Big Data has become more frequent as it allows the implementation of strategies and site selection solutions within the various business sectors.
Leaders use these techniques to make more efficient and concise decisions that generate greater profitability by maximizing revenues and optimizing costs.
Heat maps are used by any business sector to identify foot traffic and vehicular mobility patterns in an area or point of interest, as their visualization presents multiple pieces of data in a way that makes immediate sense.
Heat maps can be used to identify foot traffic patterns from a country-level scale to a more detailed level such as the infrastructure of a store or building.
Identifying mobility patterns and classifying consumers within a point of sale or areas of interest helps large retail fast fo measure foot traffic in and out of their stores while understanding the behavioral patterns of their consumers.
The correlation between location and footfall analytics, visits, sales, and the success of retailfast-food franchises have been studied and proven, so the development of this type of analysis has become a priority in the site selection process and expansion strategies.
Footfall analytics and POI characterization through Big Data are being used by retail industry leaders to make smarter business decisions, by maximizing revenue and optimizing costs.
Case Study: Footfall analysis of the largest Starbucks Coffe in Bangalore India
By applying foot traffic analytics and location intelligence techniques it becomes possible to identify urban mobility patterns for the benefit of urban planning, transportation science, and geography.
Foot traffic analytics serve as a key factor in assessing the functionality and rationality of a city’s road network or a company’s distribution center, in terms of spatial structure and connectivity.
Mobility analysis and geomarketing techniques have become key factors in the real estate investment process.
In the process of searching and selecting areas for the acquisition of a property for real estate development, investors focus on finding those with the highest expected return on investment. This process, which until now was done using traditional financial and feasibility studies, has now become incredibly simple with mobility analytics and location intelligence based on Big Data.
Pharmaceutical companies need to apply location intelligence techniques and foot traffic analytics to identify consumer mobility patterns, in order to maximize sales and generate more efficient expansion models.
The correlation between foot traffic, sales, and the success of pharmacy franchises have been studied and proven, so the development of this type of analysis has become a priority in the site selection process and expansion modeling.
Supermarkets can apply location intelligence techniques and footfall analytics to understand consumer mobility patterns, generate efficient site selection strategies, understand the performance of their stores, and estimate competitor turnover.
The correlation between foot traffic visitation, sales, and the success of retail supermarkets have been studied and proven, so the development of this type of analysis has become a priority in the site selection process and expansion modeling.
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